It’s worth noting that models [1]}, [2]} designed for VSR and VI tasks focus on how to align features from the reference frame to the given target frame, while the VFI task focuses on how to synthesize the unknown target frame from its reference frames. The unknown target frame makes the estimated intermediate flows highly uncertain, as well as affects the subsequent DConv learning. To solve this problem, in this paper, we propose to decompose the frame interpolation process into two steps, i.e. flow step and deformation step. The flow step employs a flow estimation network to estimate the intermediate flows directly and synthesize an anchor frame. The deformation step designs a PDCN to compensate for the missing details of the flow step.
Detailed network structure will be introduced in the next section.
